ArticleBMC bioinformatics2007
ProbCD: enrichment analysis accounting for categorization uncertainty.
Article in BMC bioinformatics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- A modular transcriptome map of mature B cell lymphomas.Genome medicine · 2019Article
- Optimization of gene set annotations via entropy minimization over variable clusters (EMVC).Bioinformatics (Oxford, England) · 2014Article
- timeClip: pathway analysis for time course data without replicates.BMC bioinformatics · 2014Article
- Portraying the Expression Landscapes of B-CellLymphoma-Intuitive Detection of Outlier Samples and of Molecular Subtypes.Biology · 2013Article
- Investigating the concordance of Gene Ontology terms reveals the intra- and inter-platform reproducibility of enrichment analysis.BMC bioinformatics · 2013Article
- Mining SOM expression portraits: feature selection and integrating concepts of molecular function.BioData mining · 2012Article
- Markov Chain Ontology Analysis (MCOA).BMC bioinformatics · 2012Article
- Expression cartography of human tissues using self organizing maps.BMC bioinformatics · 2011Article
- Generalized random set framework for functional enrichment analysis using primary genomics datasets.Bioinformatics (Oxford, England) · 2011Article
- ProbFAST: Probabilistic functional analysis system tool.BMC bioinformatics · 2010Article
- Comparing gene annotation enrichment tools for functional modeling of agricultural microarray data.BMC bioinformatics · 2009Article
- A general modular framework for gene set enrichment analysis.BMC bioinformatics · 2009Article
- LRpath: a logistic regression approach for identifying enriched biological groups in gene expression data.Bioinformatics (Oxford, England) · 2009Article
- Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists.Nucleic acids research · 2009Article
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2 authors.
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Abstract
backgroundAs in many other areas of science, systems biology makes extensive use of statistical association and significance estimates in contingency tables, a type of categorical data analysis known in this field as enrichment (also over-representation or enhancement) analysis. In spite of efforts to create probabilistic annotations, especially in the Gene Ontology context, or to deal with uncertainty in high throughput-based datasets, current enrichment methods largely ignore this probabilistic information since they are mainly based on variants of the Fisher Exact Test.
resultsWe developed an open-source R-based software to deal with probabilistic categorical data analysis, ProbCD, that does not require a static contingency table. The contingency table for the enrichment problem is built using the expectation of a Bernoulli Scheme stochastic process given the categorization probabilities. An on-line interface was created to allow usage by non-programmers and is available at: http://xerad.systemsbiology.net/ProbCD/.
conclusionWe present an analysis framework and software tools to address the issue of uncertainty in categorical data analysis. In particular, concerning the enrichment analysis, ProbCD can accommodate: (i) the stochastic nature of the high-throughput experimental techniques and (ii) probabilistic gene annotation.
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